title: Ability of Medicare claims data to identify nursing home patients: a validation study.
abstract: BACKGROUND
  There are currently no Medicare claims-based algorithms to identify patients receiving nursing home care (NHC). This constitutes an important limitation in outcome studies using population-based data.
  
  
  OBJECTIVE
  To assess the ability of claims data to identify patients receiving NHC, using the nursing home Minimum Data Set (MDS) as the gold standard. We hypothesized that physician claims carrying relevant Evaluation and Management (E&M) procedure codes would be an adequate source to identify nursing home patients.
  
  
  METHODS
  Cross-sectional study using the Ohio Cancer-Aging Linked Database, developed by linking records from the Ohio Cancer Incidence Surveillance System with multiple sources of data, including Medicare enrollment and claims files, and the MDS.
  
  
  METHODS
  Patients 65 years of age or older residing in Ohio, and diagnosed with incident breast, prostate, or colorectal cancer during years 1997-2001. We limited our study cohort to fee-for-service patients receiving NHC during calendar year 2002, with a look-back period in the claims data to November 2001.
  
  
  METHODS
  Sensitivity and positive predictive value (PPV).
  
  
  RESULTS
  Sensitivity, or the proportion of patients identified through the MDS file who were also successfully identified through the claims data was 88.1%. PPV, or the proportion of patients with the relevant E&M codes who were also identified in the MDS file was 83.9%.
  
  
  CONCLUSIONS
  Carrier files may be an acceptable data source to identify nursing home patients, paving the way for future risk adjustment techniques to account for nursing home status.
authors.affiliation: Department of Epidemiology and Biostatistics, School of Medicine, Case Western Reserve University, Cleveland, Ohio 44106-4945, USA. skoroukian@case.edu
authors.forename: Siran M
authors.initials: SM
authors.lastname: Koroukian
authors.forename: Fang
authors.initials: F
authors.lastname: Xu
authors.forename: Patrick
authors.initials: P
authors.lastname: Murray
mesh_terms: D000368:Aged; D000465:Algorithms; D015331:Cohort Studies; D003430:Cross-Sectional Studies; D018588:Fee-for-Service Plans; D005260:Female; D006707:Homes for the Aged / Q000706:statistics & numerical data*; D006801:Humans; D007345:Insurance Claim Review / Q000706:statistics & numerical data*; D008297:Male; D006278:Medicare / Q000706:statistics & numerical data*; D009735:Nursing Homes / Q000706:statistics & numerical data*; D015203:Reproducibility of Results; D014481:United States